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Record W2901711065 · doi:10.1521/jsyt.2018.37.2.44

Solution-Focused Brief Therapy Training: What's Useful When Training Is Brief?

2018· article· en· W2901711065 on OpenAlexvenueno aff
Marcella D. Stark, Johnny S. Kim, Peter Lehmann

Bibliographic record

VenueJournal of Systemic Therapies · 2018
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEnthusiasmSolution focused brief therapyTraining (meteorology)PsychologyMental healthPsychotherapistMedical educationBest practiceMedicineSocial psychology

Abstract

fetched live from OpenAlex

Solution-focused brief therapy (SFBT) is a strengths-based approach for developing solutions to problems through a collaborative effort to build on what has worked in the past. Mental health clinicians who have been trained in this approach focus their efforts on the competencies and resources of clients. This study reports on the SFBT training experiences of clinicians who received 40 or fewer hours of training, with an emphasis on best practices content that provided optimal learning experiences. After collecting data through an online questionnaire from 15 clinicians and follow-up interviews with six of those individuals, the researchers used an interpretive approach to identify 17 codes that were ordered into three themes: Rationale for interest in SFBT; Specific development of SFBT skills; and Maintaining enthusiasm for solution-focused practice. An overriding implication of the themes was the need to grow trainee skills through role-playing and to obtain good supervision following training. Further applications along with study limitations are identified.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.074
GPT teacher head0.306
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2018
Admission routes1
Has abstractyes

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